How To Measure Performance Of A Transit System

Transcription

1 Development of Transit Performance Measures using Big Data EDGARDO ROMÁN AFANDOR

2 Introduction Transit Systems play a very important role in: Economy, Energy consumption, Environmental issues, Social equity, Mobility, Access to jobs, education and services, etc.

3 Introduction One of transit s major roles is to provide basic mobility for those segments of the population too young, too old, or otherwise unable to drive due to physical, mental, or financial disadvantages (1). Offering the best possible transit service is not only an engineering problem, is also a social justice issue.

4 Introduction Performance measurement involves the collection, evaluation, and reporting of data that relate to how well an organization is performing its functions and meeting its goals and objectives. These tools are used to evaluate performance, identify opportunities for improvement, establish performance goals, and help guide expenditures and investments. Performance measurement and peer comparison are often initial steps in an effort to assess strengths and weaknesses and develop strategies for changing business practices. (5)

5 Introduction With the recent advances in technology, it is possible to acquire a great amount of information with relatively low cost or efforts. Several transit systems have Automatic Vehicle Locator (AVL), Automatic Fare Collection (AFC), and Automatic Passenger Counters (APC) in all or some of their vehicles. With the development of Global Positioning Systems (GPS) it is possible to include the location of the stops.

6 Introduction The information gathered can be useful as: Archived data (for planning and long term analysis) and Real-time data (for daily operation decisions, and instant quality analysis). In the past, the industry relied heavily in the use of relatively small samples, which findings had to be extrapolated to the whole phenomenon. But with the development of technology now is possible to measure the performance of a transit system not with sample data but with more comprehensive information.

7 Introduction This paper presents the results and information obtained at the San Juan Metropolitan Area (SJMA) which is an urbanized area surrounding Puerto Rico s main city and capital, San Juan. The Metropolitan Bus Authority (AMA for its Spanish acronym) is the governmental transit agency that serves the SJMA. The vehicles Capacity of 70 people standard high-floor models, where at the door there are steps which sometimes imply a longer dwelling time. The operation environment is mostly mixed traffic The network length is over 100 miles with an estimated ridership of 30,000 passengers per day.

8 Introduction

9 Introduction In the present, AMA complies with the FTA mandates in term of collection of the system performance. AMA has recently bought AVL and APC devices to install on the vehicles, but lacks the computational tools to needed to take advantage of its uses. The research aims to expand the scientific knowledge in field of transportation engineering on performance measures using real time data.

10 Introduction The objective is to finish with a feasible option that provides AMA with the computational tools capable of: Displaying real-time location of the buses, on a geo-referenced map accessible not just for AMA but also for the users through the website of the agency. Analyzing the archived data to prepare weekly, monthly and/or yearly reports on performance. Calculating a specific performance metric, on real-time that suggest real-time adjustments to the schedule base on the actual conditions on the field.

11 Methodology Three stages First development of the software necessary to connect the command center to the information on the vehicles in real time. The purpose of this stage is to be able to translate raw data into manageable figures. This software must be able to display the location of the buses on real-time onto the AMA headquarters and the Internet. The information about stops along each route has been digitalized, and saved onto a virtual data base from which the software will be operating. By the nature of this phase it has a high component of electrical and computer engineering involvement. It is important to reference that AMA had such a software and was able to archive some of the data we are using in this study, nevertheless the service was discontinued after a couple of months.

12 Methodology The raw data must be transformed, processed and analyzed

13 Methodology The second stage is the analysis of AMA performance with at least a month of archived data. From such analysis it will be stablish what specific metrics AMA should be continuously recorded in order to assess its improvement. This phase also includes the use of simulations towards the development of a new metric that AMA would be able to use on real-time to adjust their schedules. This stage has already begun by using the archived data AMA previously collected, which is already producing preliminary results. The third and final stage is the trial period on which the final product will be tested by AMA management to assess its usefulness.

14 Results Summary At present researchers have acquired one month of AVL data from main routes in service. The preliminary results show analysis of: Running time of the busses, Headway variation and adherence, From which is possible to calculate many of the basic performance metrics.

15 Results Summary

16 Results Summary

17 Results Summary The information registered will be sent to the AMA Control Center hoping to produce the following results: Several long term performance metrics for planning and reporting purposes. Passenger counts and load diagrams as well as Time-Space Diagrams will be use to establish new strategies to create express buses and incorporate new units in heavily used corridors to improve quality of service and increase the attractiveness of the public transit system. Several real-time performance metrics will be established which will assist AMA to improve the efficiency of the routes by producing alternate schedules based on the real time circumstances and variation on speed or demand. Real-time information display available to user using the internet and or in the AMA stations.

18 Intellectual Merits and Broader impacts This study aims to develop new practices for performance measurement assessment drawing from previously developed knowledge in the field. In order to address performance issue this study uses the perspective of different engineering fields such as computer and electrical engineering. Giving thus a lead in the technological advances in the field of transportation engineering.

19 Intellectual Merits and Broader impacts The implications of this study can range from maintaining and enhancing physical systems of transportation by using advanced technology, to developing new practices pertaining mobility and access for all user by integrating a social justice perspective. Both inferences have implications in policy and theory development within the context of efficiency and cost effectiveness of the transportation systems. This study also aims to cultivate leadership skills by integrating students in the decision making processes needed to develop new performance measurements in the field of transportation engineering.

20 References 1. Kittelson & Associates, Inc.; Texas Transportation Institute; KFH Group, Inc.; Parsons Brinckerhoff and Arup. TCRP Report 165: Transit Capacity and Quality of Service Manual, 3rd Edition. Transportation Research Board of the National Academies, Washington, D.C., Kittelson & Associates, Inc.; Texas Transportation Institute; and Transport Consulting, Ltd. TCRP Web-Only Document 6: Transit Capacity and Quality of Service Manual, 1 st Edition. Transportation Research Board, National Research Council, Washington, D.C., January Kittelson & Associates, Inc.; KFH Group, Inc.; Parsons Brinckerhoff Quade & Douglass, Inc.; and K. Hunter-Zaworski. TCRP Report 100: Transit Capacity and Quality of Service Manual, 2nd Edition. Transportation Research Board of the National Academies, Washington, D.C., Kittelson & Associates, Inc.; Urbitan, Inc.; Morpace International, Inc.; Queensland University of Technology and Yuko Nakanishi. TCRP Report 88: A Guidebook for Developing a Transit Performance-Measurement System, Transportation Research Board, National Research Council, Washington, DC (2003). 5. Kittelson & Associates, Inc.; Texas Transportation Institute; Yuko Nakanishi; Victoria Perk and Albert Gan. TCRP Report 141: A Methodology for Performance Measurement and Peer Comparison in the Public Transportation Industry. Transportation Research Board of the National Academies, Washington, D.C., 2010.

21 References 1) Highway Capacity Manual Transportation Research Board of the National Academies, Washington, D.C., ) National Transit Database Policy Manual. Office of Budget and Policy, Federal Transit Administration, U.S. Department of Transportation. Washington, D.C., ) Furth, P.G., B. Hemily, T.H.J. Muller, and J. Strathman. TCRP Report 113: Using Archived A VL-APC Data to Improve Transit Performance and Management. Transportation Research Board of the National Academies, Washington, D.C., ) Liao, Chen-Fu and Liu, Henry X. Development of Data-Processing Framework for Transit Performance Analysis. Transportation Research Record: Journal of the Transportation Research Board, No. 2143, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp